Team 5103 — University of Maryland
5 Competition sites
| Site | Records | Span |
|---|---|---|
| Kyoto | 837 | 812–2025 |
| Washington DC | 105 | 1921–2025 |
| Liestal | 132 | 1894–2025 |
| Vancouver | 4 | 2022–2025 |
| New York City | 2 | 2019–2025 |
3 Auxiliary sources: Japan regional (6,573), MeteoSwiss (6,642), South Korea (994)
USA-NPN enrichment — 5 extra NYC records from Washington Square Park citizen-science observations (species 228, phenophase 501)
Total: 14,598 bloom records
Enhanced features (from master dataset + NOAA CDO)
| Feature | Type |
|---|---|
| Winter / Spring mean temp | Meteorological |
| GDD Jan-Feb, GDD winter | Thermal accumulation |
| Chill hours (winter, Nov-Dec) | Dormancy requirement |
| ONI, NAO, PDO indices | Macro-climate |
| Hopkins bioclimatic index | Phenological |
| Photoperiod (Mar 20) | Astronomical |
| Lat, Long, Alt (log) | Geographic |
| Year (centered + quadratic) | Temporal trend |
Model A — Local Trend (per site)
bloom_doy ~ year + year²Model B — Pooled GAM (R pipeline)
\[\text{DOY} \sim s(\text{year}) + s(\text{lat}, \text{long}) + s(\text{alt}) + s(\text{obs}) + \text{climate} + \text{source}\]
Model B′ — Gradient Boosted Trees (Python pipeline)
Ensemble blending
Prediction intervals
Cross-language guard
Backtest MAE comparison
| Model | MAE (days) | vs Baseline |
|---|---|---|
| Local trend only | 7.27 | — |
| Baseline GAM ensemble | ~5.61 | — |
| Enhanced global (GBR) | 4.52 | +19% |
| Enhanced ensemble | 4.23 | +25% |
Key improvements:
Rising temperatures — 1.1 °C warming since pre-industrial. Warmer winters reduce chill-hour needs; warmer springs accelerate GDD → bloom advances everywhere.
ENSO — La Niña cools Pacific NW (delays Vancouver), milder Eastern US winters (advances DC/NYC). 2025-26 neutral transition → near-normal timing.
Latitude gradient — ~1 DOY delay per degree N above 35°N. GAM’s lat-long smooth captures this.
Altitude penalty — ~2 days later per 100 m elevation. Liestal (350 m) systematically later than sea-level sites.
Kyoto: Urban heat island + 0.2 d/century advancement. 1200-yr record stabilises local model.
Washington DC: Tidal Basin thermal buffer → earliest bloomer. 2.2 d/decade recent acceleration.
Liestal: Alpine amplified warming (0.3 °C/decade). Foehn winds cause stochastic early bloom → widest variability.
Vancouver: PDO phase modulates decadal variability. Maritime buffering keeps volatility moderate.
NYC: Shortest record (12 yrs) → highest uncertainty. Continental cold snaps reset GDD accumulation. NPN data fusion reduces LOO MAE by ~1.5 days.
| City | DOY | Date | Interval | Width |
|---|---|---|---|---|
| Washington DC | 84 | Mar 25, 2026 | Mar 17 – Apr 01 | 15 |
| Liestal | 86 | Mar 27, 2026 | Mar 19 – Apr 05 | 17 |
| Kyoto | 88 | Mar 29, 2026 | Mar 20 – Apr 07 | 18 |
| Vancouver | 90 | Mar 31, 2026 | Mar 21 – Apr 10 | 20 |
| New York City | 92 | Apr 02, 2026 | Mar 25 – Apr 09 | 15 |
| Metric | Value |
|---|---|
| Backtest MAE (enhanced) | 4.23 days |
| R vs Python gap | 2.8 days |
| Sum of squared widths (SSW) | 1463 |
| Cross-site spread | 8 days |
| Blend method | Averaged R + Python |
| City | Baseline | Enhanced | Shift |
|---|---|---|---|
| Kyoto | DOY 88 (18d) | DOY 94 (12d) | +6 d |
| Liestal | DOY 86 (17d) | DOY 95 (10d) | +9 d |
| New York City | DOY 92 (15d) | DOY 98 (11d) | +6 d |
| Vancouver | DOY 90 (20d) | DOY 95 (25d) | +5 d |
| Washington DC | DOY 84 (15d) | DOY 89 (13d) | +5 d |
What the enhanced model adds:
Why enhanced predictions are later:
Tighter intervals (12.2 d avg vs 15.4 d baseline):
Cherry Blossom Peak Bloom Prediction 2026
Code, data, and outputs: github.com/GMU-CherryBlossomCompetition
Team 5103 · University of Maryland